A dynamic dispatching method for emergency resources in reservoir dam emergency scenarios

Abstract

The invention discloses a method for dynamic dispatching of emergency resources under a reservoir dam emergency scenario. The method comprises the following steps: performing flood evolution simulation under an emergency scenario, constructing a flood-road network coupling model including information of roads, resettlement points, flood flow velocity and water depth; predicting the number of disaster victims according to the scenario information, and then calculating resource demand according to a resource demand prediction model; determining a resource allocation correlation coefficient; introducing a resource demand coefficient and a disaster severity coefficient, and constructing an emergency resource fairness index based on a Gini coefficient; determining an optimal route from a resource storage point to a resettlement point, and constructing an emergency resource transportation efficiency index based on the optimal route; constructing an emergency resource dispatching model with dispatching fairness and transportation efficiency as objective functions, and obtaining a dispatching scheme under a dynamic scenario by solving the dispatching model; and the dispatching scheme of the invention has a good overall view and is more in line with the actual needs of the emergency scenario.

Description

Technical Field

[0001] The invention relates to a dynamic dispatching method for emergency resources in a reservoir dam emergency event scenario, belonging to the technical field of resource dispatching and allocation in reservoir emergency management of water conservancy engineering technology. Background Art

[0002] The emergency management of reservoir dam emergencies needs scientific emergency response technology support to form a systematic and effective response strategy throughout the entire process of the incident. Emergency response measures, as driving factors throughout the scenario, include emergency rescue measures to prevent or delay dam failure and emergency rescue measures to mitigate the consequences of disasters. Among emergency rescue technologies, the most critical is the dispatching technology to ensure the demand for emergency resources.

[0003] Emergency resource scheduling models mostly use fairness, rescue time, and scheduling costs as optimization objectives. However, in the early stages of a reservoir dam emergency, the emergency resource reserve capacity is limited, and different disaster-stricken areas have different demands for rescue resources. In addition, the uncertainty in the evolution of the emergency may result in the scheduling plan being unable to meet the actual needs generated by the evolution of the emergency scenario. Summary of the invention

[0004] Purpose of the invention: In view of the problems and shortcomings in the prior art, the emergency resource scheduling model based on scenario analysis is studied to determine the rescue resource needs under dynamic scenarios and formulate a resource scheduling plan that fits the development of the scenario. The present invention provides a method for dynamic scheduling of emergency resources under reservoir dam emergency scenarios. The method of the present invention complies with the basic principles of emergency resource scheduling of maximizing time efficiency, dynamic scenario, and interest coordination. The formulated emergency resource scheduling plan takes into account the severity of the disaster and the resource demand level of the resettlement site. Compared with the traditional scheduling model, it ensures the maximization of the emergency rescue effect. The fairness of emergency resource allocation is guaranteed while taking into account the scheduling efficiency. The scheduling plan has a good overall view and is more in line with the actual needs of the emergency scenario.

[0005] Technical solution: A method for dynamic dispatching of emergency resources in a reservoir dam emergency scenario, comprising the following steps:

[0006] Step 1: Simulate flood evolution under emergency scenarios

[0007] Through flood evolution, risk indicators such as discharge flow, flood velocity and water depth, and flooded area under flood conditions are obtained.

[0008] Step 2: Calculation results coupled with road network information

[0009] Graph theory is used to transform the road network into a mathematical expression that can be read by the algorithm. The risk indicators in the flood evolution simulation are coupled with the road network information to construct a flood-road network coupling model that includes information such as roads, resettlement points, flood flow velocity, and water depth.

[0010] Step 3: Determine emergency resource requirements under emergency scenarios

[0011] After a reservoir dam emergency scenario occurs, the number of affected people is predicted based on the scenario information, and then the consumable and non-consumable resource demands are calculated based on the resource demand prediction model.

[0012] Step 4: Determine the correlation coefficient of resource allocation

[0013] At present, the most widely used model for emergency resource allocation is the fairness-efficiency model based on humanistic care. This model does not take into account the transportation time of emergency supplies and the severity of different disaster-stricken areas. The dam-break flood evolves from the dam site to the downstream. The farther the disaster-stricken area is from the dam site, the more time it has to evacuate. As the flood energy is lost, the impact and destructive capacity gradually decreases. The severity of the disaster in different areas is significantly different.

[0014] In order to quantitatively analyze the priority of resource dispatch, that is, the more severely affected the disaster area is, the higher the resource satisfaction rate should be, and the dispatch time should be shorter, the disaster severity coefficient a and resource demand coefficient b are introduced. The mortality rate of the affected population is used as the disaster severity coefficient to judge the disaster situation in the disaster area; the demand coefficients of different types of resources are determined to measure the urgency of resource demand;

[0015] After a reservoir dam emergency occurs, the needs of different resources in different disaster-stricken areas in the downstream flooding area vary in importance. For example, medical rescue resources have a higher priority than living resources, and drinking water is more urgent than tents and food in living resources. Determine the demand coefficient of typical emergency resources, which include drinking water, convenient food, tents, and life jackets; the corresponding demand levels of drinking water, convenient food, tents, and life jackets are 1.2, 1.0, 0.8, and 1.5, respectively.

[0016] Step 5: Build an emergency resource scheduling model

[0017] First, the resource demand coefficient and disaster severity coefficient are introduced to construct an emergency resource fairness index based on the Gini coefficient. Second, the optimal route from the resource storage point to the resettlement point can be determined through the path dynamic optimization algorithm, and an emergency resource transportation efficiency index based on the optimal route can be constructed. An emergency resource scheduling model is constructed with scheduling fairness and transportation efficiency as the objective function.

[0018] Step 6: Construct and solve the emergency resource scheduling model

[0019] The constructed emergency resource scheduling model is solved to obtain the distribution quantity of different materials at each resettlement point.

[0020] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for dynamic dispatching of emergency resources in a reservoir dam emergency scenario as described above are implemented.

[0021] A computer-readable storage medium stores a computer program for executing the above-mentioned method for dynamic dispatching of emergency resources in a reservoir dam emergency scenario.

[0022] Beneficial effects: The dynamic dispatching method of emergency resources in the reservoir dam emergency scenario provided by the present invention follows the emergency resource dispatching principles of maximizing time efficiency, dynamic situational characteristics, and interest coordination. Since the reservoir dam breach flood evolves from the dam site to the downstream, the farther the disaster-stricken area is from the dam site, the more sufficient the evacuation time is, and with the loss of flood energy, the impact and destructive capacity gradually decreases, and the severity of disasters in different areas is significantly different. Therefore, in order to quantitatively analyze the priorities of resource dispatch, that is, the higher the degree of disaster, the higher the resource satisfaction rate should be, and the dispatching time should be shorter. Compared with the previous dispatching model, the transportation time of emergency materials and the impact of the severity of different disaster-stricken areas are taken into account, and the disaster severity coefficient a and the resource demand coefficient b are introduced. The solution of the dispatching model not only ensures the fairness of emergency resource allocation but also takes into account the dispatching efficiency. The dispatching plan has a good overall view and is more in line with the actual needs of the emergency scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a location map of the placement points and material points in the embodiment of the present invention;

[0024] Figure 2 It is a bar chart of the emergency resource satisfaction rate of each resettlement point in the embodiment of the present invention. DETAILED DESCRIPTION

[0025] The present invention is further explained below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading the present invention, various equivalent forms of modifications to the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

[0026] The dynamic dispatching method of emergency resources under the emergency scenario of reservoir dam includes the following steps:

[0027] Step 1: Conduct flood evolution simulation under emergency scenarios

[0028] Through flood evolution simulation, risk indicators such as discharge flow, flood velocity and water depth, and inundated area under flood conditions are obtained, among which flood evolution simulation technology belongs to the existing technology.

[0029] Step 2: Calculation results coupled with road network information

[0030] Graph theory is used to transform the road network into a mathematical expression that can be read by the algorithm, and the flood evolution risk index is coupled with the road network information to construct a flood-road network coupling model that includes information such as roads, resettlement points, flood flow velocity, and water depth:

[0031] G=(N,E,S,M,ND,ED) (1)

[0032] In the formula, G It is a flood-road network coupling model; N is a node set, corresponding to the intersection in the real road network, such as N i express i node; S It is a gathering place for resettlement and an evacuation point for people in the disaster area set up in the plan, such as S i Indicates the placement point i ; M It is a collection point for material distribution and a center for the collection and distribution of emergency materials, such as M i Indicates material distribution point i ; E is a set of road segments, mapped to the actual road network, such as E ij Representation Node i , j The road sections between ND is the node attribute value, including the time when the flood reaches the node FT , flood depth FS , flood flow information FV ; ED Road attribute value, including road length L , Driving speed V .

[0033] Step 3: Determine emergency resource requirements under emergency scenarios

[0034] After a reservoir dam emergency scenario occurs, it is necessary to predict the number of affected people based on the scenario information, and then calculate the consumable and non-consumable resource demands based on the resource demand prediction model.

[0035] 3-1 Estimated number of people affected

[0036] The flood inundation range and inundation depth information in the flood evolution simulation results are extracted. When the inundation depth reaches the set value, the population density method is used to estimate the affected population. The calculation formula is as follows:

[0037] (1)

[0038] Where P i For resettlement point i The number of people affected by the disaster; j Risk Area j Population density of the unit, people / km 2 ; A j For unit j Inundation range, km 2 This method assumes that the population within the calculation unit is evenly distributed, and the calculation accuracy is closely related to the size of the calculation unit. The smaller the calculation unit, the higher the estimation accuracy.

[0039] 3-2 Calculation of emergency resource requirements

[0040] Establish a demand forecast model for consumable and non-consumable resources, and incorporate the seasonal coefficient into the calculation of emergency resources. The specific formula is as follows:

[0041] (2)

[0042] In the formula, For the scenario k Disaster Point i Resources for emergency response j The demand is divided into consumption resources CES and non-consumable resources NES ; t The time interval until the next resource scheduling; α j Provide disaster-affected people with resources per unit time j per capita demand; For the scenario k Disaster Point i Number of people affected by the disaster; Q i is the seasonal coefficient; β j Provide non-consumable resources for disaster victims j per capita demand; The remaining amount of resources consumed for the previous scenario; For the n Dispatched to the disaster site i Resources j quantity.

[0043] Step 4: Determine the correlation coefficient of resource allocation

[0044] Determine the disaster severity factor a and resource requirement coefficient b , quantitatively analyze the priorities of resource scheduling, that is, the more severely affected the disaster area is, the higher the resource satisfaction rate should be, and the scheduling time should be shorter.

[0045] 4-1 Disaster severity coefficient

[0046] The main targets of post-disaster rescue are the people affected by the disaster, and the main principle of resource allocation is people-oriented. Therefore, the mortality rate of the affected population is used as the coefficient of disaster severity to judge the disaster situation in the affected area.

[0047] 4-2 Resource Requirement Coefficient

[0048] After a reservoir dam emergency occurs, the demands for different resources in different disaster-stricken areas downstream of the flooding area vary in importance. For example, medical rescue resources have a higher priority than living resources, and drinking water is more urgent than tents and food in living resources. Determine the demand coefficients of typical emergency resources, which include drinking water, convenience foods, tents, and life jackets; the corresponding demand levels for drinking water, convenience foods, tents, and life jackets are 1.2, 1.0, 0.8, and 1.5, respectively. Step 5: Construct an emergency resource scheduling model

[0049] 5-1 Assumptions

[0050] According to the background of emergency rescue for sudden incidents in reservoirs and dams, the following assumptions are established for the emergency resource dispatch model: the locations of various emergency resource distribution points in the disaster-stricken area are known, and the reserve quantity is clear; due to the weak economy of emergency rescue, the dispatch cost issue is not considered; the transportation time does not consider traffic conditions such as weather and congestion; the transportation vehicles at each distribution point have sufficient transportation capacity.

[0051] 5-2 Emergency resource fairness index based on the Gini coefficient

[0052] The consequences of sudden incidents at reservoir dams are serious. The flood inundation covers a wide area, and the number of people affected downstream is large. The emergency reserve resources at the beginning of the scenario usually cannot cover all needs. Emergency resource scheduling needs to weigh various factors and make reasonable allocations to ensure the best effect of emergency activities. While ensuring that the emergency demand satisfaction rate of the disaster-stricken points is maximized, fairness must also be taken into account, that is, the severity of the disaster at the disaster-stricken points and the degree of demand for different types of resources need to be considered. Based on this problem, the Gini coefficient, an economic income fairness evaluation indicator, is used to measure the fairness of the resource satisfaction rate of each disaster-stricken point. The traditional fairness model does not take into account the resource demand level and the severity of the disaster-stricken area. The embodiment of the present invention introduces the resource demand coefficient and the disaster severity coefficient, and constructs an emergency resource fairness index based on the Gini coefficient as shown below:

[0053] (3)

[0054] (4)

[0055] (5)

[0056] In the formula, U 1 is the fairness objective function; For the scenario k Lower settlement point i The disaster severity coefficient; b j For resources j The corresponding demand coefficient; For the scenario k Next, resource point w Assigned to resettlement site i Resources j the number of For the scenario k Next, the settlement point i About Resources j The demand for ij For disaster-stricken areas j About Resources i satisfaction rate; Provide emergency resources for disaster-affected areas i The mean of satisfaction rate; n The number of disaster-affected points; I is the number of resettlement points; W The number of resource points.

[0057] 5-3 Emergency resource transportation efficiency indicators based on optimal routes

[0058] Based on the flood-road network coupling model, the optimal route from the resource storage point to the resettlement point can be determined through the dynamic path optimization algorithm, and the transportation time from each resource storage point to the resettlement point can be calculated. In order to optimize the transportation efficiency through emergency resource scheduling and ensure that emergency resources are transported to the disaster site in the shortest time, an emergency resource transportation efficiency index based on the optimal route is constructed, and the formula is as follows:

[0059] (6)

[0060] In the formula, U 2 is the transportation efficiency objective function; For the scenario k Next, resource point w Assigned to resettlement site i Resources j the number of For the scenario k Lower settlement point i The disaster severity coefficient; b j For resources j The corresponding demand coefficient; For the scenario k Next, resource point w To the resettlement site i The time required for transportation;n The number of disaster-affected points; I is the number of resettlement points; W The number of resource points.

[0061] 5-4 Construction of emergency resource scheduling model

[0062] Based on the assumptions in 5-1, an emergency resource scheduling model was constructed with scheduling fairness and transportation efficiency as the objective functions, as follows:

[0063] (7)

[0064] (8)

[0065] The constraints are:

[0066] (9)

[0067] (10)

[0068] (11)

[0069] In the formula, represents the reserves of material j at storage point w; n The number of disaster-affected points; I is the number of resettlement points; W is the number of resource points; formulas (7) and (8) are the objective functions of emergency resource scheduling, which ensure fairness and transportation efficiency respectively; formula (9) is that the total amount of resources scheduled is equal to its storage capacity; formula (10) is the number of disaster points j About Resources i The satisfaction rate of the disaster-affected point for emergency resources; Formula (11) is i The mean satisfaction rate.

[0070] Step 6: Solving the emergency resource scheduling model

[0071] The constructed emergency resource scheduling model is solved to obtain the distribution quantity of different materials at each resettlement point.

[0072] Emergency resources refer to the general term for various types of resources required in the emergency response process when an emergency occurs at a reservoir or dam, and can be divided into flood control and emergency rescue resources and rescue resources. Flood control and emergency rescue resources refer to the resources required for engineering rescue measures, specifically including sand and gravel, geosynthetics, bulldozers, etc. Rescue resources refer to the resources required for rescuing downstream people, including daily necessities, medical supplies, rescue teams, etc. Reservoir and dam management units usually reserve necessary engineering rescue materials according to the needs of emergency rescue work, and specify the resource storage location and the dispatch of rescue teams in the emergency plan. Therefore, the present invention mainly studies the allocation of daily necessities, rescue supplies and medical supplies required for rescuing downstream people. The dispatch of emergency resources is closely related to the evolution of scenarios, and the types and quantities of resource requirements are different in different scenario periods. According to the purpose, it can be divided into life, medical and rescue categories. According to the usage, it can be divided into disposable consumable resources and recyclable sustainable resources. According to the degree of urgency, they can be divided into emergency resources and non-emergency resources. Emergency resources are resources for maintaining the life and health of disaster victims and carrying out rescue work, and their priority is the highest. Non-emergency resources refer to resources that will not cause serious consequences if they are in short supply within a certain period of time, and a certain time lag is allowed. The specific resource details are shown in Table 1.

[0073] Table 1 Classification of emergency resources by purpose

[0074]

[0075] Example:

[0076] If a dam burst occurs due to a pipe burst in a certain reservoir, the dam burst flood will flood the downstream area of ​​956.44 km 2 , involving 30 towns. In order to protect the lives of the public and respond to the emergency transfer of the affected people downstream, the reservoir emergency plan has set up 27 resettlement points. According to the severity of the disaster and the number of people affected, 5 typical resettlement points and 3 resource distribution points were selected. After the emergency scenario occurs, four typical emergency resources, drinking water, convenience food, tents, and life jackets, are dispatched from the resource distribution points to the resettlement points. The locations of the resettlement points and resource distribution points are as follows: Figure 1 shown.

[0077] To calculate the resource demand of each resettlement site, it is necessary to determine the number of disaster victims at each resettlement site. The population density method was used to calculate the number of disaster victims at each resettlement site, which were 48302, 41221, 33463, 57447, and 44593, respectively. The demand for drinking water is 1.6L per person per day, the demand for convenience food is 3 packs per person per day, the demand for tents is 0.5 per person, and the demand for life jackets is 0.05 per person based on the level of major flood disasters in the "Regulations for the Preparation of Flood Control Material Reserve Quotas". Based on the per capita demand and the seasonal coefficient in summer, the time interval for consumables is 2 days, and the emergency resource demand for each resettlement site is determined, see Table 2.

[0078] Table 2 Emergency resource demand under the 10,000-year piping dam breach scenario

[0079]

[0080] Scheduling model parameters

[0081] Based on the simulation results of the dam break flood evolution, the basic data required for the calculation of population mortality rate were extracted. The downstream people’s understanding of the severity of the flood was conservatively taken as fuzzy, and the disaster severity coefficient was determined. The specific values ​​are shown in Table 3.

[0082] Table 3 Disaster severity coefficients for each resettlement site

[0083]

[0084] Due to the suddenness of reservoir dam emergency scenarios, the demand for emergency resources changes with the scenario. Usually, the resources at the distribution points cannot meet the needs of each resettlement point at the beginning of the scenario. Therefore, assuming that after the emergency scenario occurs, the total amount of resources raised in the national emergency resource storage and in a short period of time is 60% of the demand, Table 4 shows the resource reserves of the three distribution points.

[0085] Table 4 The reserves of emergency resources at various distribution points

[0086]

[0087] The locations of the resettlement points and resource distribution points are known. Based on the road network information in the flood evolution scenario model, the path dynamic optimization method proposed in the previous article is used to determine the optimal transportation path from the distribution point to the resettlement point. The transportation distance is shown in Table 5.

[0088] Table 5 Transportation distance from distribution point to resettlement point (km)

[0089]

[0090] Model solution and result analysis

[0091] According to the emergency information of reservoir dam incidents, an emergency resource dispatch model was constructed. This model is a dual-objective dispatch model of dispatch fairness and transportation efficiency. According to the principle of hierarchical sequence method, the primary objective dispatch fairness function was first solved, and then the optimal solution was used as the constraint function to solve the transportation efficiency function. The generated dispatch scheme is shown in Table 6. The satisfaction rate of each resettlement point is shown in Figure 2 shown.

[0092] Table 6 Emergency resource scheduling plan

[0093]

[0094] Depend on Figure 2 It can be seen that for the same resource, the satisfaction rate of the resettlement points with higher disaster severity is higher. For example, the drinking water resource satisfaction rate of resettlement point 1 with the highest disaster severity is 84%, while the drinking water resource satisfaction rate of resettlement point 5 with the lowest disaster severity is 46%. This reflects the priority of emergency resource scheduling. The more severe the disaster, the more emergency resources the resettlement points will obtain, so as to ensure the overall maximization of rescue efficiency. The higher the demand coefficient of emergency resources, the more obvious the difference in resource satisfaction rate at different resettlement points. For example, the highest and lowest satisfaction rates of life jacket resources with the highest demand coefficient are 88% and 44% respectively, while the highest and lowest satisfaction rates of tent resources with the lowest demand coefficient are 75% and 52% respectively. This reflects that the rescue effects of different emergency resources are taken into consideration when scheduling resources, and the scheduling of living resources is more even than that of rescue resources, so as to ensure the rationality and fairness of resource allocation. Table 6 gives the scheduling scheme for the four types of resources from the distribution point to the resettlement point. This scheduling scheme follows the principle of optimal scheduling efficiency, giving priority to distributing resources from the nearest distribution point to the resettlement point. For example, the resources of resettlement point 1 are mainly distributed by the nearest distribution point 1, and when the reserves are insufficient, they are distributed by other distribution points. Since the disaster severity coefficient is introduced into the scheduling efficiency model, the target optimization will focus on the resettlement points with higher disaster severity. Although the overall transportation efficiency of the scheduling result considering the disaster severity is not the optimal solution, it improves the rescue efficiency of the resettlement points with higher disaster severity, which reflects the principle of the highest rescue efficiency.

[0095] In summary, the emergency resource scheduling scheme proposed in this invention takes into account the severity of the disaster at the resettlement site and the resource demand level, and ensures the maximization of the emergency rescue effect compared with the traditional scheduling model. The engineering scenario application shows that the solution of the scheduling model not only ensures the fairness of emergency resource allocation but also takes into account the scheduling efficiency. The scheduling scheme has a good overall view and is more in line with the actual needs of the emergency scenario, which verifies the rationality and effectiveness of this method.

[0096] Obviously, those skilled in the art should understand that the above-mentioned methods for dynamic dispatching of emergency resources in the reservoir dam emergency scenario of the embodiment of the present invention can be implemented by a general computing device, which can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices. Optionally, they can be implemented by executable program codes of computing devices, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. In this way, the embodiments of the present invention are not limited to any specific combination of hardware and software.

Claims

1. A method for dynamic dispatching of emergency resources in a reservoir dam emergency scenario, characterized in that: The steps include: Step 1: Simulate flood evolution under emergency scenarios; Obtain risk indicators under flood conditions through flood evolution; the risk indicators include discharge flow, flood velocity and water depth, and flooded area; Step 2: Calculate the result and couple it with the road network information; Graph theory is used to convert the road network into a mathematical expression that can be read by the algorithm, and the risk indicators in the flood evolution simulation are coupled with the road network information to construct a flood-road network coupling model that includes roads, resettlement points, flood flow velocity, and water depth information; Step 3: Determine the emergency resource requirements under the emergency scenario; After a reservoir dam emergency scenario occurs, the number of people affected is predicted based on the scenario information, and then the consumable and non-consumable resource requirements are calculated based on the resource demand prediction model; Step 4: Determine the resource allocation correlation coefficient; The mortality rate of the affected population is used as the disaster severity coefficient to judge the disaster situation in the affected area; the demand coefficients of different types of resources are determined to measure the urgency of resource demand; Step 5: Construct an emergency resource scheduling model; First, the resource demand coefficient and disaster severity coefficient were introduced to construct an emergency resource fairness index based on the Gini coefficient. Second, the optimal route from the resource storage point to the resettlement point was determined through a dynamic path optimization algorithm, and an emergency resource transportation efficiency index based on the optimal route was constructed. An emergency resource scheduling model was constructed with scheduling fairness and transportation efficiency as the objective function. Step 6: Construct and solve the emergency resource scheduling model; Solve the constructed emergency resource scheduling model to obtain the distribution quantity of different materials at each resettlement point; In the step 5, according to the emergency rescue background of reservoir dam incidents, the following assumptions are established for the emergency resource scheduling model: the locations of the emergency resource distribution points in the disaster-stricken area are known, and the reserve volume is clear; the transportation capacity of the transportation vehicles at each distribution point meets the emergency resource scheduling needs; the emergency resource scheduling model is constructed with scheduling fairness and transportation efficiency as the objective function, as follows: （7）； （8）； The constraints are: （9）； （10）； （11）； In the formula, represents the reserves of material type j at storage point w; n The number of disaster-affected points; I is the number of resettlement points; W is the number of resource points; formulas (7) and (8) are the objective functions of emergency resource scheduling, which ensure fairness and transportation efficiency respectively; formula (9) is that the total amount of resources scheduled is equal to its storage capacity; Formula (10) is the disaster point j About Resources i The satisfaction rate of the disaster-affected point for emergency resources; Formula (11) is i The mean satisfaction rate.

2. The method for dynamic dispatching of emergency resources under reservoir dam emergency scenarios according to claim 1, characterized in that: The flood-road network coupling model including roads, resettlement points, flood velocity, and water depth information is: G=(N,E,S,M,ND,ED) , where: G It is a flood-road network coupling model; N is a set of nodes, corresponding to the intersections in the real road network; S It is a gathering place for resettlement and an evacuation point for people in the disaster area set up in the emergency plan; M It is a collection point for material distribution and a center for the collection and distribution of emergency materials; E It is a set of road sections, mapped to the actual road network; ND is the node attribute value, including the time when the flood reaches the node FT , flood depth FS , flood flow information FV ; ED Road attribute value, including road length L , Driving speed V .

3. The method for dynamic dispatching of emergency resources under reservoir dam emergency scenarios according to claim 1, characterized in that: The step three includes the following contents: 3-1 Prediction of number of people affected by the disaster; The flood inundation range and inundation depth information in the flood evolution simulation results are extracted. When the inundation depth reaches the set value, the population density method is used to estimate the affected population. The calculation formula is as follows: （1）； Where P i For resettlement point i The number of people affected by the disaster; j Risk Area j Population density of the unit, people / km 2 ; A j For unit j Inundation range, km 2 ; 3-2 Calculation of emergency resource requirements; Establish a demand forecast model for consumable and non-consumable resources, and incorporate the seasonal coefficient into the calculation of emergency resources. The specific formula is as follows: （2）； In the formula, For the scenario k Disaster Point i Resources for emergency response j The demand is divided into consumption resources CES and non-consumable resources NES ; t The time interval until the next resource scheduling; α j Provide disaster-affected people with resources per unit time j per capita demand; For the scenario k Disaster Point i Number of people affected by the disaster; Q i is the seasonal coefficient; β j Provide non-consumable resources for disaster victims j per capita demand; The remaining amount of resources consumed for the previous scenario; For the n Dispatched to the disaster site i Resources j quantity.

4. The method for dynamic dispatching of emergency resources under reservoir dam emergency scenarios according to claim 1, characterized in that: In the step 5: By introducing the resource demand coefficient and the disaster severity coefficient, the emergency resource fairness index based on the Gini coefficient is constructed as follows: （3）； （4）； （5）； In the formula, U 1 is the fairness objective function; For the scenario k Lower settlement point i The disaster severity coefficient; b j For resources j The corresponding demand coefficient; For the scenario k Next, resource point w Assigned to resettlement site i Resources j the number of For the scenario k Next, the settlement point i About Resources j The demand for ij For disaster-stricken areas j About Resources i satisfaction rate; Provide emergency resources for disaster-affected areas i The mean of satisfaction rate; n The number of disaster-affected points; I is the number of resettlement points; W is the number of resource points; Construct an emergency resource transportation efficiency index based on the optimal route. The formula is as follows: （6）； In the formula, U 2 is the transportation efficiency objective function; For the scenario k Next, resource point w Assigned to resettlement site i Resources j the number of For the scenario k Lower settlement point i The disaster severity coefficient; b j For resources j The corresponding demand coefficient; For the scenario k Next, resource point w To the resettlement site i The time required for transportation; n The number of disaster-affected points; I is the number of resettlement points; W The number of resource points.

5. A computer device, characterized in that: The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for dynamic scheduling of emergency resources in a reservoir dam emergency scenario as described in any one of claims 1 to 4 are implemented.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for executing the method for dynamic dispatching of emergency resources in a reservoir dam emergency event scenario as described in any one of claims 1-4.

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